Aggregation and analytics for application-specific optimization based on multiple data sources

Abstract

Aggregating and transforming data, and performing analytics thereupon, for application-specific optimization based on multiple data sources. The data is preferably ingressed automatically, and may originate from various public and/or private data sources. Data transformation preferably aligns the data aggregated from the various sources, to thereby allow meaningful referencing. Complex and non-aligned data can therefore be consolidated, such that it is readily digestible by simulation (or other) software. In an embodiment, risk of flooding for a supply chain is computed from the aggregated and transformed data, using data analytics based on physical computation for flood risk assessment, allowing the supply chain to be optimized with regard to threat of flooding and/or actual flooding. In another embodiment, risk of wild fire may be assessed. Other types of risk may also be assessed.

The invention claimed is: 
     
       1. A method for aggregating and transforming data from multiple sources, comprising:
 determining a location of interest for natural disaster risk analysis; 
 determining a plurality of sources of data that describe a physical environment of the location; 
 automatically ingressing, from selected ones of the plurality of sources, the data that describes the physical environment, wherein the ingressed data from at least a first of the selected ones comprises topography data pertaining to the location, the topography data formatted as a plurality of grid cells; 
 programmatically transforming the ingressed data into data maps that are aligned to one another to allow referencing therebetween, further comprising: 
 programmatically performing a watershed delineation process to determine, from the ingressed topography data, a watershed area for each of at least one watershed pertaining to the location; and 
 programmatically removing, from the ingressed topography data, particular ones of the grid cells which do not include any of the at least one determined watershed area and which therefore do not directly contribute to precipitation run-off that can potentially reach the location of interest; 
 evaluating risk of natural disaster pertaining to the location by using the aligned data maps as input to an evaluator selected from the group consisting of a simulation model and an analytic process; and 
 comparing output of the evaluator to a first threshold and setting a risk of natural disaster to a highest level if the output exceeds the first threshold, and otherwise comparing the output of the evaluator to a second threshold and setting the risk of natural disaster to an intermediate level if the output exceeds the second threshold. 
 
     
     
       2. The method according to  claim 1 , wherein:
 the location is provided using longitude and latitude values; and 
 determining the plurality of sources comprises: 
 reverse geocoding the longitude and latitude values to determine identifying name information associated with the location; and 
 locating the sources which provide suitable data for a geographical region corresponding to the identifying name information. 
 
     
     
       3. The method according to  claim 1 , wherein:
 the location is provided using coordinates; and 
 determining the plurality of sources comprises: 
 using the coordinates to access a mapping which correlates the coordinates with identifying name information associated with the location; and 
 locating the sources which provide suitable data for a geographical region corresponding to the identifying name information. 
 
     
     
       4. The method according to  claim 1 , wherein the automatically ingressing comprises using session cookies to allow coordinated non-interactive download over a period of time, from the selected ones, of the data that describes the physical environment. 
     
     
       5. The method according to  claim 1 , wherein the programmatically transforming further comprises programmatically changing a resolution of the ingressed data from at least the first of the selected ones to align with a resolution of the ingressed data from at least a second of the selected ones prior to performing the watershed delineation process. 
     
     
       6. The method according to  claim 1 , wherein the programmatically transforming further comprises programmatically changing a resolution of the ingressed data from the first of the selected ones to align with a resolution of reference data for the location prior to performing the watershed delineation process. 
     
     
       7. The method according to  claim 1 , wherein the programmatically transforming further comprises programmatically removing at least one noise artifact from the ingressed data from at least the first of the selected ones prior to performing the watershed delineation process. 
     
     
       8. The method according to  claim 7 , wherein:
 the programmatically removing the at least one noise artifact comprises first identifying, in the ingressed topography data, the at least one noise artifact as being irrelevant to underlying topography of the location and therefore comprising a noise artifact to be removed from the ingressed topography data. 
 
     
     
       9. The method according to  claim 1 , wherein:
 the programmatically transforming further comprises aligning the topography data from the first of the selected ones and a second of the selected ones to have an identical number of pixels and to match an identical geo-location of a reference topography data prior to performing the watershed delineation process. 
 
     
     
       10. The method according to  claim 1 , wherein the programmatically transforming further comprises programmatically extracting at least one feature from the ingressed data from at least the first of the selected ones. 
     
     
       11. The method according to  claim 10 , wherein:
 the ingressed data from the first of the selected ones comprises land use data pertaining to the location; 
 the at least one feature describes use of land at or near the location; and 
 the programmatically extracting comprises removing, from the land use data, the at least one feature from the ingressed data to allow focus on the land use data for the location. 
 
     
     
       12. The method according to  claim 10 , wherein:
 the ingressed data from at least the first of the selected ones comprises soil data pertaining to the location; and 
 the evaluating comprises: 
 determining, from the soil data, soil infiltration information pertaining to the location; and 
 using the soil infiltration information when determining the risk. 
 
     
     
       13. The method according to  claim 1 , wherein:
 the ingressed data from at least the first of the selected ones comprises historical data pertaining to the location; and 
 the programmatically transforming comprises programmatically cleansing the ingressed historical data, prior to performing the watershed delineation process, such that a resulting one of the data maps has unsuitable information removed therefrom. 
 
     
     
       14. The method according to  claim 1 , wherein:
 the grid cells in the ingressed data are organized as a plurality of grids; and 
 the programmatically transforming further comprises programmatically overlaying data of a first of the grids with data of a second of the grids, responsive to determining that the data of the second grid is of a better quality that the data of the first grid, prior to performing the watershed delineation process. 
 
     
     
       15. The method according to  claim 1 , wherein the location pertains to a supply chain and the evaluating risk evaluates a risk of flooding for the supply chain. 
     
     
       16. The method according to  claim 1 , wherein the evaluating risk evaluates a risk of wild fire for the location. 
     
     
       17. A method for aggregating and transforming data from multiple sources, comprising:
 determining a location of interest for natural disaster risk analysis; 
 determining a plurality of sources of data that describe a physical environment of the location; 
 automatically ingressing, from selected ones of the plurality of sources, the data that describes the physical environment, wherein the ingressed data from at least a first of the selected ones and a second of the selected ones comprises topography data pertaining to the location; 
 programmatically transforming the ingressed data into data maps that are aligned to one another to allow referencing therebetween, further comprising aligning the topography data from the first of the selected ones and the second of the selected ones to have an identical number of pixels and to match an identical geo-location of a reference topography data; 
 evaluating risk of natural disaster pertaining to the location by using the aligned data maps as input to an evaluator selected from the group consisting of a simulation model and an analytic process, further comprising: 
 programmatically determining, from the topography data, canopy interception information pertaining to the location; and 
 using the canopy interception information when determining the risk by determining an impact of physical canopy present at the location of interest on an amount of rainfall that reaches a ground surface at the location; and 
 comparing output of the evaluator to a first threshold and setting a risk of natural disaster to a highest level if the output exceeds the first threshold, and otherwise comparing the output of the evaluator to a second threshold and setting the risk of natural disaster to an intermediate level if the output exceeds the second threshold. 
 
     
     
       18. The method according to  claim 17 , wherein the location pertains to a supply chain and the evaluating risk evaluates a risk of flooding for the supply chain. 
     
     
       19. The method according to  claim 17 , wherein the evaluating risk evaluates a risk of wild fire for the location.